Accurate and reliable methods of memory error detection and recovery are becoming increasingly necessary as robotic surgical technology expands. Memory errors are often caused in nonvolatile memory of end effectors of robotic surgical systems by elevated temperatures such as those produced by an autoclave during sterilization of an end effector. In sensitive applications, such as robotic surgical systems, memory errors can cause malfunction of the robotic surgical systems. Malfunction of the robotic surgical system during surgery can have severe health-related and financial consequences for patients, surgeons, and hospitals. Furthermore, when such memory errors occur in end effectors, the error is typically addressed using manual human intervention thereby causing inconvenience for end users and prolonged lack of operability of the robotic surgical system. As such, there is a need to address at least the aforementioned problems.